ID 原文 译文
38986 实验结果表明，提出算法的跟踪精度明显要优于传统的基于广义协方差交集(Generalized Covariance Intersection，GCI)的分布式融合算法以及粒子多伯努利跟踪算法，具有较好的跟踪性能。 The experimental results show that the proposed algorithm has a better tracking accuracy than the traditional GCI-based distributed fusion algorithm and the traditional particle filter MB(PF-MB) tracking algorithm, with a good multi-target tracking ability in complex environments.
38987 GPS(Global Positioning System)接收机中，常用的捕获方法有时域串行捕获方法、基于FFT(Fast Fourier Transform)的并行频率捕获方法和基于FFT的并行码相位捕获方法，但在某些应用场景下，会对卫星信号的捕获速度提出更高的要求，因此给出了一种基于相关的SFFT(Sparse Fast Fourier Transform)的卫星信号快速捕获算法。 In GPS(Global Positioning System)receivers, commonly used acquisition methods are time-domain serial acquisition methods, FFT(Fast Fourier Transform)-based parallel frequency acquisition methods and FFT-based parallel code phase acquisition methods, but in certain application scenarios, it will put forward higher requirements on the acquisition speed of satellite signals, so a satellite signal fast acquisition algorithm based on correlated SFFT(Sparse Fast Fourier Transform) is given.
38988 该算法结合卫星信号伪随机码的强自相关性的特性，将原有的SFFT的幅度估值去掉，利用时域串行的捕获方法，将SFFT算法中输出的大值坐标点对应的本地伪码与接收卫星信号做相关，进而捕获卫星信号。 This algorithm combined the strong autocorrelation characteristic of the satellite signal pseudo-random code, removed the original SFFT amplitude estimate, and used the time-domain serial capture method to convert the local pseudo-corresponding to the large-valued coordinate points output by the SFFT algorithm The code is correlated with the received satellite signal to capture the satellite signal.
38989 通过实验对算法进行验证，并与已有的卫星信号捕获方法进行对比，结果表明该方法能有效地运用于卫星信号捕获中，并且该算法的运算量要比传统捕获算法更低。 The algorithm is verified through experiments and compared with the existing satellite signal acquisition methods. The results show that the method can be effectively used in satellite signal acquisition, and the calculation amount of the algorithm is lower than the traditional acquisition algorithm.
38990 为改善低信噪比条件下LDPC码闭集识别的性能，本文提出了一种基于最大余弦比的软判决识别算法。 In order to improve the performance of LDPC code closed-set recognition with low signal-to-noise ratio, this paper proposes a soft decision recognition algorithm based on maximum cosine ratio.
38991 该算法在分析了最大均值似然比算法存在的问题的基础上，利用LDPC码的编码结构特点，将识别过程归结为二元域中线性关系的检测问题; Based on the analysis of the problems of the maximum mean likelihood ratio algorithm, the algorithm uses the coding structure characteristics of the LDPC code to reduce the recognition process to the detection problem of the linear relationship in the binary domain;
38992 同时引入能够有效表征线性编码约束关系成立可能性大小的余弦检验函数，基于正确校验矩阵与错误校验矩阵下的余弦检验函数统计特性不同的事实，将两种情况下的余弦比作为编码器判定依据，从而实现低信噪比下LDPC码闭集的有效识别。 At the same time, a cosine test function that can effectively characterize the possibility of the establishment of linear coding constraints is introduced, based on the fact that the statistical characteristics of the cosine test function under the correct check matrix and the error check matrix are different, and use the cosine ratio in both cases as the basis for encoder determination, thereby achieving low signal-to-noise ratio effective identification of closed sets of LDPC codes.
38993 仿真结果表明，在信噪比为0 dB条件下，算法能够可靠识别出常用的IEEE802.16e协议中LDPC码， The simulation results show that the algorithm can reliably identify the commonly used LDPC codes in IEEE802.16 e protocol under the condition of 0 dB signal-to-noise ratio.
38994 同时与现有算法相比，算法性能提升近1 dB。 At the same time, the performance of the algorithm is improved by nearly 1 dB compared with the existing algorithm.
38995 多机器人任务规划是多机器人系统研究的主要问题之一，多目标多机器人任务规划是指同时对多机器人系统的多个指标进行优化。 Multi-robot mission planning is one of the main problems in multi-robot system research. Multi-objective multi-robot mission planning refers to optimizing multiple indicators of the multi-robot system at the same time.